Yuncheng Li
Computer Vision and Pattern Recognition · 2015–2019
A researcher in the Science corpus: 7 papers; trusts 581 researchers and is trusted by 19 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 121 citations into it; #19,388 of 21,575 by trust here, #7,027 by citations
- Artificial Intelligence — 78 citations into it; #9,764 of 35,345 by trust here, #3,835 by citations
- Natural Language Processing — 28 citations into it
- Evaluation & Benchmarks — 26 citations into it
- Computational Mechanics — 22 citations into it; #3,150 of 10,001 by trust here, #1,409 by citations
- Optimization & Training — 22 citations into it; #1,140 of 2,601 by trust here, #507 by citations
- Representation & Self-Supervised Learning — 12 citations into it
- Model Architectures — 10 citations into it
Whom Yuncheng Li trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Kaiming He
- Ilya Sutskever
- Yoshua Bengio
- Karen Simonyan
- Ross B. Girshick
- Yann LeCun
- Diederik P. Kingma
- Andrew Zisserman
Who trusts Yuncheng Li overall
- Lu Jiang
- Ang Li
- Yunseok Jang
- Zhou Zhao
- Lin Wang
- Chenyou Fan
- Görkem Algan
- Zhilu Zhang
- Sean Welleck
- Ryuichiro Hataya
Papers from Yuncheng Li's perspective
Ordered by how strongly the researchers Yuncheng Li trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- TGIF: A New Dataset and Benchmark on Animated GIF Description (2016) — 314 citations
- 3D Hand Shape and Pose Estimation From a Single RGB Image (2019) — 504 citations
- Learning from Noisy Labels with Distillation (2017) — 593 citations
- Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization (2015) — 537 citations
- Improving Pairwise Ranking for Multi-label Image Classification (2017) — 234 citations
- Deciphering the 2016 U.S. Presidential Campaign in the Twitter Sphere: A Comparison of the Trumpists and Clintonists (2016) — 70 citations
- Dynamic Kernel Distillation for Efficient Pose Estimation in Videos (2019) — 78 citations